Imagine this: as lunch time approaches, Dave peruses vegetarian menu options at a local quick service restaurant (QSR) from his desktop, placing an order of veggie burger with no cheese, and a cookie in his cart. In a rush to get to a meeting, he must exit out before completing the order. As the meeting progresses, the usual hot and sunny Bay Area temperature drops to a windy 68℉. When the meeting ends, Dave pulls out his phone to see a notification from the QSR’s app:
“It’s feeling a little cold outside. Warm yourself! Add a hot cappuccino to your order.”
When he taps the notification, he is brought to his cart, which has the same veggie burger, cookie, and customizations saved, along with the option to add a cappuccino. Impressed with the restaurant’s timely offer for a warm beverage, Dave accepts the promotion, and using his card on file, seamlessly completes the order.
What you just read was real-time omni-channel marketing in action. For today’s on-the-go customer, oftentimes where an order begins is not where it ends—and the options for engagement are only increasing. After all, 70% of QSR operators intend to invest more in customer-facing technology to enable online or app ordering, mobile payments, and delivery management. That’s where an omni-channel approach to customer engagement comes into play. From the desktop to the mobile device to in-person ordering, omni-channel personalization means delivering relevant, seamless, and targeted experiences no matter where the customer engages.
However, true personalization goes beyond the omni-channel approach. Effective 1:1 personalized engagement also requires consideration of the customer’s in-the-moment context. This context includes a wide range of environmental factors such as weather, time of day, and location to determine the right promotion to serve up. As we read in the above-mentioned scenario, a sudden drop in temperature in the summertime in the Bay Area may feel cool, prompting a cross-sell of cappuccino.
Restaurants and convenience stores can also leverage location intelligence and proximity data to serve up location-centric information and promotions to drive customer traffic to a particular location. These decisions, made based on the real-time context of their customers and their locations, keep wait times down for lasting satisfaction and loyalty.
This level of personalization requires extraction of a large volume of ever-evolving data by zip code on temperature, season, location, and time. It is then paired with a customer’s in-the-moment context to use by-day historical averages to identify if it “feels cold” or “feels hot” at that location in that moment to offer real-time guidance.
Similarly, to enable location-based customer interactions, restaurants and convenience stores must understand the distribution of app users by zip code and DMA code, and create dynamic segments based on location proximity. When location permissions are shared, they must be able to recognize when customers are in new areas and adjust recommendations accordingly. At the same time, when location permissions are not shared then the company may have to partner with a solution provider that can use ML to ascertain the best location of a customer and deliver the appropriate experience.
For instance, suppose Dave drives from San Jose CA to San Francisco in the late afternoon to attend a meeting. Unbeknown to him, his favorite coffee shop has a free coffee offer going on between 3 p.m. and 6 p.m. Dave is very privacy conscious and has not enabled location permission on his phone. So, how can the coffee shop reach out to him if it cannot determine his location? An intelligent customer engagement platform can do this by calculating Dave’s best location and ensure that this broadcast announcement reaches him when he enters San Francisco, irrespective of permissions.
“Welcome to San Francisco, Dave! Enjoy a free cup of coffee on us today. Hurry, the offer ends at 6 p.m. …”
While gathering such intelligence might sound like a tall order, today’s AI and ML technologies can definitely make it happen. And the results of such real-time engagement are well worth it — a top QSR achieved a 31% boost in on-site traffic when it updated its ads according to changes in the weather. Additionally, it is forecasted that location targeting will grow to $38.7 billion by 2022.
However, for a successful real-time and omni-channel approach to customer engagement, it isn’t enough to simply be where the customer is. A restaurant or store must also offer up what the customers are looking for or what they usually prefer. Critical for doing so is the company’s ability to leverage historic data and loyalty program participation across devices—starting first with the mobile app.
As a channel specific to the individual customer, the mobile device enables companies to serve up push notifications or in-app messages that are tailored to each customer, no matter where the customer engages. For example, say a customer typically stops by your drive-thru between noon and 1 p.m., but that tends to be a high-traffic time for the drive-thru. Then you could send this customer a promotion via their loyalty app for a free side, redeemable in-restaurant only. When the customer enters the restaurant, this reward is then seamlessly served up, regardless of if he places his order at a kiosk, tablet, or the front register.
As quick service restaurants and convenience stores continue to embrace new channels by which to engage customers, they must also consider how to deliver seamless, in-the-moment personalized experiences no matter where a customer interacts. That’s where ZineOne comes in. Through our AI-powered Intelligent Customer Engagement (ICE) platform, we provide enterprises with the omni-channel personalization needed to leverage more successful and satisfactory customer experiences. Contact ZineOne today to learn how our engagement experts can accelerate engagement and ROI at your company.